A Review of Geographic Information System and Remote Sensing with Applications to the Epidemiology and Control of Schistosomiasis in China
Overview
Affiliations
Geographic information system (GIS) and remote sensing (RS) technologies offer new opportunities for rapid assessment of endemic areas, provision of reliable estimates of populations at risk, prediction of disease distributions in areas that lack baseline data and are difficult to access, and guidance of intervention strategies, so that scarce resources can be allocated in a cost-effective manner. Here, we focus on the epidemiology and control of schistosomiasis in China and review GIS and RS applications to date. These include mapping prevalence and intensity data of Schistosoma japonicum at a large scale, and identifying and predicting suitable habitats for Oncomelania hupensis, the intermediate host snail of S. japonicum, at a small scale. Other prominent applications have been the prediction of infection risk due to ecological transformations, particularly those induced by floods and water resource developments, and the potential impact of climate change. We also discuss the limitations of the previous work, and outline potential new applications of GIS and RS techniques, namely quantitative GIS, WebGIS, and utilization of emerging satellite information, as they hold promise to further enhance infection risk mapping and disease prediction. Finally, we stress current research needs to overcome some of the remaining challenges of GIS and RS applications for schistosomiasis, so that further and sustained progress can be made to control this disease in China and elsewhere.
Ogunsakin R, Babalola B, Olusola J, Joshua A, Okpeku M Parasitol Res. 2024; 123(7):262.
PMID: 38970660 PMC: 11227462. DOI: 10.1007/s00436-024-08276-0.
Goldblatt R, Holz N, Tate G, Sherman K, Ghebremicael S, Bhuyan S medRxiv. 2023; .
PMID: 37986844 PMC: 10659457. DOI: 10.1101/2023.11.06.23298044.
Digital health for climate change mitigation and response: a scoping review.
Rahimi-Ardabili H, Magrabi F, Coiera E J Am Med Inform Assoc. 2022; 29(12):2140-2152.
PMID: 35960171 PMC: 9667157. DOI: 10.1093/jamia/ocac134.
From the One Health Perspective: Schistosomiasis Japonica and Flooding.
Guo S, Li L, Zhang L, Li Y, Li S, Xu J Pathogens. 2021; 10(12).
PMID: 34959493 PMC: 8709050. DOI: 10.3390/pathogens10121538.
Gong Y, Zhu L, Li Y, Zhang L, Xue J, Xia S Infect Dis Poverty. 2021; 10(1):88.
PMID: 34176515 PMC: 8237418. DOI: 10.1186/s40249-021-00874-9.